learn_error

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses the key side effect of auto-synthesizing a prevention rule into the rules table, which aligns with the readOnlyHint=false annotation. However, it does not clarify whether repeated calls with the same pattern create duplicate rules or are deduplicated, and it omits any mention of idempotency or potential side effects on existing data.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that efficiently communicates the core functionality and the auto-synthesis behavior. It avoids unnecessary detail, though it could be slightly more structured by separating the parameter list from the side-effect explanation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (8 parameters, side effects, pattern detection), the description provides insufficient context. It does not explain how the pattern is determined, what the rules table looks like, or the relationship with sibling tools like self_error_log or workflow_learn. The absence of an output schema and lack of examples further reduces completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description lists the required parameters (file, error, root_cause, fix, pattern) but does not explain their meaning or relationships, and the schema has no descriptions. Optional parameters like project, category, and severity are not mentioned at all, leaving their semantics unclear. The parameter names are self-explanatory but not fully defined, especially 'pattern' and how it differs from 'error'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Structured error capture' and lists the key parameters, making the tool's purpose apparent. However, it does not explicitly name the verb 'record' or 'log', relying on the phrase 'error capture' to imply the action, which is a minor gap.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions that after N errors with the same pattern, a prevention rule is auto-synthesized, hinting at when the tool's output becomes useful. But it does not explicitly state when to use this tool versus alternatives (e.g., self_error_log) or when not to use it, leaving usage guidance vague.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.